There are a large number of applications where knowledge of the 3D profile of an object is relevant. Different techniques exist for scanning the profile of an object. Basically they can be subdivided into radar based systems, ultrasound based systems and optical sensing systems.
Radar based systems have the advantage that they can sense a long range but have the disadvantage that they have a poor angular and depth resolution with regard to certain applications (e.g. for tracking the profile in a road).
Ultrasound based systems can be useful for short range sensing but their narrow bandwidth limits the depth sensitivity and the sampling resolution and the strong absorption in air limits the range to a few meters.
Optical sensing based methods can be subdivided in different types measuring the distance through time of flight measurements or by triangulation.
In time of flight methods the object is illuminated by a light source. From the delay between the emission and the detection the distance traveled by the light can be determined. The time of flight methods can make use of pulsed illumination.
In triangulation based systems, the unknown position of an object is calculated using trigonometry. An example of such a system is the Kinect system of Microsoft described in U.S. Pat. No. 8,320,621. In this system structured infra-red light (e.g. circles) is projected and viewed with a 3D camera. This system, which is primarily intended for indoor gaming and entertainment applications, is not suitable for outdoor use, due to the intensity of the sunlight.
In stereovision the distance to an object is determined from the local shift between corresponding parts in the images obtained by two cameras under different viewing angles or by one stereo camera with two lenses. Stereovision based systems can make use of existing set-ups and algorithms from robot vision, can operate using ambient illumination, and do not require projection. On the other hand stereovision based systems have the disadvantage that calibrated cameras with sufficient distance are required. Furthermore, sufficient structure in the images is required to enable cross correlation for parallax, it is difficult to detect flat surfaces and water, a sufficient number of pixels is required, the depth sensitivity is limited, and typical cameras have insufficient dynamic range to cope with various light conditions. The biggest hurdle seems to be that stereovision based systems cannot work if there is insufficient structure in the object being scanned.
US 2005/195383 A1 discloses a method for obtaining information about objects in an environment around a vehicle in which infrared light is emitted into a portion of the environment and received and the distance between the vehicle and objects from which the infrared light is reflected is measured. An identification of each object from which light is reflected is determined and a three-dimensional representation of the portion of the environment is created based on the measured distance and the determined identification of the object. Icons representative of the objects and their position relative to the vehicle are displayed on a display visible to the driver based on the three-dimensional representation. Additionally or alternatively to the display of icons, a vehicular system can be controlled or adjusted based on the relative position and optionally velocity of the vehicle and objects in the environment around the vehicle to avoid collisions.
US 2007/177011 A1 relates to a movement control system which can be used to control moving platforms such as vehicles or robotic arms. It especially applies to a driving aid for vehicles and to a parking aid capable of self-parking a vehicle. A three-dimensional camera is located on the platform, say a car and arranged to view the environment around the platform. A processor uses the three-dimensional information to create a model of the environment which is used to generate a movement control signal. Preferably the platform moves relative to the environment and acquires a plurality of images of the environment from different positions.
US 2012/038903 A1 provides methods and systems for adaptively controlling the illumination of a scene. In particular, a scene is illuminated, and light reflected from the scene is detected. Information regarding levels of light intensity received by different pixels of a multiple pixel detector, corresponding to different areas within a scene, and/or information regarding a range to an area within a scene, is received. That information is then used as a feedback signal to control levels of illumination within the scene. More particularly, different areas of the scene can be provided with different levels of illumination in response to the feedback signal.
The systems mentioned above are not capable of operating sufficiently accurately at a high vehicle speed for a long detection range.
Therefore there is still room for improvement of surround sensing scan systems that can be used in outdoor situations scanning the profile of objects over a large range with a high resolution and with a high speed.
An improved system is described in European patent application no. 13175826.0 and international patent application no. PCT/EP2014/064769 (unpublished at the date of filing of the present application) in the name of the present applicant. The present application discloses further improvements relating to the capturing and detection of images, which can be used in systems such as the one of the aforementioned patent applications.